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Updated: Jul 8, 2025

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使用可解释的机器学习模型与可穿戴传感器数据和生活方式因素预测正子发射断层扫描脑粉样蛋白的阳性

Noriyuki Kimura1, Tomoki Aota2, Yasuhiro Aso3

  • 1Department of Neurology, Faculty of Medicine, Oita University, Idaigaoka 1-1, Hasama, Yufu, Oita, 879-5593, Japan. noriyuki@oita-u.ac.jp.

Alzheimer's research & therapy
|December 13, 2023
PubMed
概括

机器学习模型使用生活方式因素和可穿戴传感器预测大脑粉样蛋白负担升高. 这种非侵入性查方法有助于在老年人中早期发现阿尔茨海默病.

关键词:
粉样蛋白阳性的一致性生活方式因素 生活方式因素机器学习 机器学习轻度认知障碍 轻度认知障碍在PiB-PET中使用.可穿戴式传感器传感器

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